Computer-Assisted Pattern Analysis of Domenico Scarlatti's Keyboard Sonatas

Enabling new research on the Baroque composer by facilitating quantitative approaches

Computer Science
Data Development
Music Studies
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Domenico Scarlatti’s 555 keyboard sonatas hold the confusing honor of being, as W. Dean Sutcliffe phrased it, “one of the greatest but least well understood and covered repertories of Western keyboard music.” A confluence of many factors seem to have led to this gap between importance and understanding. One of the main factors is the size, impenetrability, and density of the corpus of sonatas. This seems to have proven daunting for experts in musicology who may be used to more qualitative methods.

Lumbroso and his team believe the key to unlocking new, serious scholarship on Scarlatti’s keyboard sonatas is to turn to quantitative methods and plan to employ computer science expertise on the processing of Big Data streams, to process a subset of the sonatas, and to establish a framework for the structural analysis of these sonatas. The proposal will be based on:

  • The curation of an open-source machine-readable dataset of the keyboard sonatas, such as to enable a new generation of scholars to study the sonatas using existing tools (such as music21, etc.).
  • The creation of a set of open-source scripts for the extraction and categorization of rhythmic micro-patterns and structural macro-patterns within the sonatas

Team

Project Director

Grants

2020–2022

Dataset Curation